Code vulnerability detection method and system based on code translation large model

By employing a code translation-based large model approach, utilizing multiple translation large models and similarity calculations, and combining them with the XGBoost model for code vulnerability detection, the problem of low detection efficiency and poor accuracy in existing technologies is solved, achieving efficient and accurate vulnerability detection for multiple programming languages.

CN121765729APending Publication Date: 2026-03-31HUAZHONG UNIV OF SCI & TECH
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Patent Information

Application Number
CN202511878010.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-12-12
Publication Date
2026-03-31

AI Technical Summary

Technical Problem

Existing static and dynamic code analysis methods are inefficient in detecting code vulnerabilities and are prone to missed or false detections, making them ineffective in detecting vulnerabilities in multiple programming languages.

Method used

We adopt a code translation big model-based approach, which uses multiple big translation models to perform code translation and similarity calculation. Combined with preprocessing and feature extraction, we use an XGBoost binary classification model for vulnerability detection to assist the big translation models and improve detection accuracy.

Benefits of technology

It achieves efficient and accurate code vulnerability detection for multiple programming languages, improving detection efficiency and accuracy, and reducing false positives and false negatives.

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Abstract

The invention belongs to the technical field of code vulnerability detection, and particularly relates to a code vulnerability detection method and system based on a code translation large model. According to the method, on the basis of an initial programming language type and a target programming language type, forward translation and reverse translation processing is carried out on a to-be-translated code through a plurality of translation large models; according to the method and the device, the target similarity between each code to be translated and the corresponding reverse output code is obtained, and the similarity vector sequence is constructed based on the target similarity between each code to be translated and the corresponding reverse output code, so that the vulnerability occurrence probability of the similarity vector sequence can be obtained through the code vulnerability detection model, and whether multiple types of codes to be translated have vulnerabilities or not can be accurately judged. The method has the advantages of multiple detectable programming language types, high detection efficiency and high detection accuracy.
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